This thesis describes one of the first measurements made at CERN’s Large Hadron Collider, the world's largest and highest-energy particle collider. The method of analysis described in the first part is applied to the first CMS collision data collected after the LHC startup in 2010 and leads to the first experimental result for the inclusive b cross section using semileptonic decays at a center of mass energy of 7 TeV. The second part of the thesis describes the building and testing of the barrel pixel detector; the author herself played an important role in its construction, commissioning and first exploitation. The CMS collaboration Thesis Award Committee selected this work as the best thesis of the year 2010

^ 74 GeV and |y| 2.4; the b jets must contain a B hadron. The measurement has significant statistics up to p T ∼ O(TeV). Advanced methods of unfolding are performed to extract the signal. It is found that fixed-order calculations with underlying event describe the measurement well.

This informative monograph describes the technological evolution of silicon detectors and their impact on high energy particle physics. The author here marshals his own first-hand experience in the development and also the realization of the DELPHI, CDF II and the CMS tracking detector. The basic principles of small strip- and pixel-detectors are presented and also the final large-scale applications. The Evolution of Silicon Detector Technology acquaints readers with the manifold challenges involving the design of sensors and pushing this technology to the limits. The expert will find critical information that is so far only available in various slide presentation scattered over the world wide web. This practical introduction of silicon sensor technology and its day to day life in the lab also offers many examples to illustrate problems and their solutions over several detector generations. The new edition gives a detailed overview of the silicon sensor technology used at the LHC, from basic principles to actual implementation to lessons learned.

This book addresses the fundamental principles of interaction between radiation and matter, the principles of working and the operation of particle detectors based on silicon solid state devices. It covers a broad scope in the fields of application of radiation detectors based on silicon solid state devices from low to high energy physics experiments, including in outer space and in the medical environment. This book also covers state-of-the-art detection techniques in the use of radiation detectors based on silicon solid state devices and their readout electronics, including the latest developments on pixelated silicon radiation detector and their application.The content and coverage of the book benefit from the extensive experience of the two authors who have made significant contributions as researchers as well as in teaching physics students in various universities.

Beam test results with a highly granular Analog Hadron Calorimeter Prototype (AHCAL) / S. Morozov -- Validation of the hadronic calibration of the ATLAS calorimeter with test beam data corresponding to the pseudorapidity range 2.5

The exploration of the subnuclear world is done through increasingly complex experiments covering a wide range of energy and performed in a large variety of environments from particle accelerators, underground detectors to satellites and space laboratory. The achievement of these research programs calls for novel techniques, new materials and instrumentation to be used in detectors, often of large scale. Therefore, fundamental physics is at the forefront of technological advance and also leads to many applications. Among these, medical applications have a particular importance due to health and social benefits they bring to the public.

​In order to cope with the increased radiation level and the challenging pile-up conditions at High Luminosity-LHC, the CMS collaboration will replace its current calorimeter endcaps with the High Granularity Calorimeter (HGCAL) in the mid 2020s. This dissertation addresses two important topics related to the preparation of the HGCAL upgrade: experimental validation of its silicon- based design and fast simulation of its data. Beam tests at the DESY (Hamburg) and the CERN SPS beam test facilities in 2018 have been the basis for the design validation. The associated experimental infrastructure, the algorithms deployed in the reconstruction of the recorded data, as well as the respective analyses are reported in this thesis: First, core components of the silicon-based prototype modules are characterised and it is demonstrated that the assembled modules are functional. In particular, their efficiency to detect minimum ionising particles (MIPs) traversing the silicon sensors is found to be more than 98% for most of the modules. No indication of charge sharing between the silicon pads is observed. Subsequently, the energy response is calibrated in situ using the beam test data. Equalisation of the different responses among the readout channels is achieved with MIPs hereby deploying the HGCAL prototype as a MIP-tracking device. The relative variation of the inferred calibration constants amounts to 3% for channels on the same readout chip. The calibration of the time-of-arrival information is performed with an external time reference detector. With it, timing resolutions of single cells including the full prototype readout chain around 60ps in the asymptotic high energy limit are obtained. The calorimetric performance of the HGCAL prototype is validated with particle showers induced by incident positrons and charged pions. For electromagnetic showers, the constant term in the relative energy resolution is measured to be (0.52± 0.08) %, whereas the stochastic term amounts to (22.2 ± 0.3)% √GeV. This result is in good agreement with the calorimeter simulation with GEANT4. The prototype’s positioning resolution of the shower axis, after subtracting the contribution from the delay wire chambers in the beam line used as reference, is found to be below 0.4 mm at 300 GeV. At the same energy, the angular resolution in the reconstruction of the electromagnetic shower axis in this prototype is measured to be less than 5mrad. The analysis of the hadronic showers in this thesis makes use state-of-the- art machine-learning methods that exploit the calorimeter’s granularity. It is indicated that the energy resolution may be improved using software compensation and also that the separation of electromagnetic and charged pion-induced showers in the calorimeter may benefit from such methods. The measurements of the hadronic showers are adequately reproduced by GEANT4 simulation. Altogether, the obtained results from the analysis of the beam test data in this thesis are in agreement with the full functionality of the silicon-based HGCAL design. The final part of this thesis provides a proof of principle that generative modelling based on deep neural networks in conjunction with the Wasserstein distance is a suitable approach for the fast simulation of HGCAL data: Instead of sequential simulation, a deep neural network-based generative model generates all calorimeter energy depositions simultaneously. This genera t or network is optimised throu gh an adversarial training process using a critic network guided by the Wasserstein distance. The developed framework in this thesis is applied to both GEANT4- simulated electromagnetic showers and to positron data from the beam tests. Ultimately, this fast simulation approach is up to four orders of magnitude faster than sequential simulation with GEANT4. It is able to produce realistic calorimeter energy depositions from electromagnetic showers, incorporating their fluctuations and correlations when converted into typical calorimeter observables.